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囊性纤维化作为一种系统性疾病的数学模型。

Mathematical models of cystic fibrosis as a systemic disease.

机构信息

Center for Engineering Innovation, The University of Texas at Dallas, Richardson, Texas, USA.

Department of Biomedical Engineering, Georgia Tech and Emory University, Atlanta, Georgia, USA.

出版信息

WIREs Mech Dis. 2023 Nov-Dec;15(6):e1625. doi: 10.1002/wsbm.1625. Epub 2023 Aug 6.

DOI:10.1002/wsbm.1625
PMID:37544654
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10843793/
Abstract

Cystic fibrosis (CF) is widely known as a disease of the lung, even though it is in truth a systemic disease, whose symptoms typically manifest in gastrointestinal dysfunction first. CF ultimately impairs not only the pancreas and intestine but also the lungs, gonads, liver, kidneys, bones, and the cardiovascular system. It is caused by one of several mutations in the gene of the epithelial ion channel protein CFTR. Intense research and improved antimicrobial treatments during the past eight decades have steadily increased the predicted life expectancy of a person with CF (pwCF) from a few weeks to over 50 years. Moreover, several drugs ameliorating the sequelae of the disease have become available in recent years, and notable treatments of the root cause of the disease have recently generated substantial improvements in health for some but not all pwCF. Yet, numerous fundamental questions remain unanswered. Complicating CF, for instance in the lung, is the fact that the associated insufficient chloride secretion typically perturbs the electrochemical balance across epithelia and, in the airways, leads to the accumulation of thick, viscous mucus and mucus plaques that cannot be cleared effectively and provide a rich breeding ground for a spectrum of bacterial and fungal communities. The subsequent infections often become chronic and respond poorly to antibiotic treatments, with outcomes sometimes only weakly correlated with the drug susceptibility of the target pathogen. Furthermore, in contrast to rapidly resolved acute infections with a single target pathogen, chronic infections commonly involve multi-species bacterial communities, called "infection microbiomes," that develop their own ecological and evolutionary dynamics. It is presently impossible to devise mathematical models of CF in its entirety, but it is feasible to design models for many of the distinct drivers of the disease. Building upon these growing yet isolated modeling efforts, we discuss in the following the feasibility of a multi-scale modeling framework, known as template-and-anchor modeling, that allows the gradual integration of refined sub-models with different granularity. The article first reviews the most important biomedical aspects of CF and subsequently describes mathematical modeling approaches that already exist or have the potential to deepen our understanding of the multitude aspects of the disease and their interrelationships. The conceptual ideas behind the approaches proposed here do not only pertain to CF but are translatable to other systemic diseases. This article is categorized under: Congenital Diseases > Computational Models.

摘要

囊性纤维化(CF)被广泛认为是一种肺部疾病,尽管它实际上是一种全身性疾病,其症状最初表现为胃肠道功能障碍。CF 最终不仅会损害胰腺和肠道,还会损害肺、性腺、肝脏、肾脏、骨骼和心血管系统。它是由 CFTR 上皮离子通道蛋白基因的几种突变之一引起的。在过去的 80 年中,通过深入研究和改进抗菌治疗,CF 患者(pwCF)的预期寿命从数周稳步增加到 50 多年以上。此外,近年来出现了几种改善疾病后遗症的药物,最近对疾病根本原因的显著治疗为一些但不是所有 pwCF 带来了健康的显著改善。然而,仍有许多基本问题没有得到解答。例如,在肺部,CF 的复杂性在于相关的氯离子分泌不足通常会扰乱上皮细胞的电化学平衡,并导致粘稠、粘性的粘液在气道中积聚,这些粘液不能有效地清除,并为各种细菌和真菌群落提供了丰富的滋生地。随后的感染通常会变成慢性感染,对抗生素治疗反应不佳,其结果有时与目标病原体的药物敏感性只有微弱的相关性。此外,与具有单一目标病原体的快速解决的急性感染不同,慢性感染通常涉及多种细菌群落,称为“感染微生物组”,它们会发展出自己的生态和进化动态。目前还不可能设计出完整的 CF 数学模型,但可以为疾病的许多不同驱动因素设计模型。在这些不断发展但孤立的建模工作的基础上,我们在下文中讨论了一种多尺度建模框架(称为模板和锚点建模)的可行性,该框架允许逐步整合具有不同粒度的细化子模型。本文首先回顾了 CF 的最重要的生物医学方面,然后描述了现有的数学建模方法或具有加深我们对疾病的多个方面及其相互关系的理解的潜力。本文提出的方法背后的概念不仅适用于 CF,而且可以转化为其他系统性疾病。本文属于以下分类:先天性疾病>计算模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdca/10843793/2f947e2835a6/nihms-1920596-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdca/10843793/fbeb8b99eb98/nihms-1920596-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdca/10843793/2f947e2835a6/nihms-1920596-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdca/10843793/fbeb8b99eb98/nihms-1920596-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cdca/10843793/2f947e2835a6/nihms-1920596-f0003.jpg

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